[HTML][HTML] Feedback on a shared big dataset for intelligent TBM Part I: Feature extraction and machine learning methods
This review summarizes the research outcomes and findings documented in 45 journal
papers using a shared tunnel boring machine (TBM) dataset for performance prediction and …
papers using a shared tunnel boring machine (TBM) dataset for performance prediction and …
Machine learning to inform tunnelling operations: Recent advances and future trends
BB Sheil, SK Suryasentana… - Proceedings of the …, 2020 - icevirtuallibrary.com
The proliferation of data collected by modern tunnel-boring machines (TBMs) presents a
substantial opportunity for the application of machine learning (ML) to support the decision …
substantial opportunity for the application of machine learning (ML) to support the decision …
Shield attitude prediction based on Bayesian-LGBM machine learning
Effective shield attitude control is essential for the quality and safety of shield construction.
The traditional shield attitude control method is manual control based on a driver's …
The traditional shield attitude control method is manual control based on a driver's …
Success and challenges in predicting TBM penetration rate using recurrent neural networks
Abstract Tunnel Boring Machines (TBMs) have been increasingly used in tunnelling
projects. Forecasting future TBM performance would be desirable for project time …
projects. Forecasting future TBM performance would be desirable for project time …
Ensemble regression based on polynomial regression-based decision tree and its application in the in-situ data of tunnel boring machine
Regression is an important branch of engineering data mining tasks, aiming to establish a
regression model to predict the output of interest based on the input variables. To meet the …
regression model to predict the output of interest based on the input variables. To meet the …
Recurrent neural networks for real-time prediction of TBM operating parameters
With tunnel boring machines (TBMs) widely used in tunnel construction, the adaptable
adjustment of TBM operating status has become a research focus. Since the prediction of …
adjustment of TBM operating status has become a research focus. Since the prediction of …
Hard-rock tunnel lithology prediction with TBM construction big data using a global-attention-mechanism-based LSTM network
The TBM-constructed rock tunnel often suffers from low comparability of efficiency between
geological condition detection and the TBM real-time operation requirements. This article …
geological condition detection and the TBM real-time operation requirements. This article …
An adaptive hierarchical decomposition-based method for multi-step cutterhead torque forecast of shield machine
Cutterhead torque is generated by interaction between geological environment and shield
machine, which is one of the main load parameters of shield machine during the tunneling …
machine, which is one of the main load parameters of shield machine during the tunneling …
A multi-channel decoupled deep neural network for tunnel boring machine torque and thrust prediction
Accurate prediction of thrust and torque plays a crucial role in the control parameters
optimization and intelligent tunneling of tunnel boring machines (TBMs). Currently …
optimization and intelligent tunneling of tunnel boring machines (TBMs). Currently …
A comparative study of different machine learning algorithms in predicting EPB shield behaviour: a case study at the Xi'an metro, China
XD Bai, WC Cheng, G Li - Acta geotechnica, 2021 - Springer
Complex geological conditions and/or inappropriate shield tunnel boring machine (TBM)
operation can significantly degrade both the excavation and safety of tunnel construction. In …
operation can significantly degrade both the excavation and safety of tunnel construction. In …